Used virtual metrology for predicting semi conductor manufacturing properties for the process Ion Implant
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Updated
Aug 10, 2018 - Jupyter Notebook
Used virtual metrology for predicting semi conductor manufacturing properties for the process Ion Implant
MI-QVM Trial Version – Quality Virtual Metrology solution by MiRLE, enabling fast evaluation of model performance for smart manufacturing.
Confidence-aware inspection-decision engine for semiconductor manufacturing — AI virtual metrology with a statistically-guaranteed reliability budget, realized as a synthesized FPGA IP (DACR-IP).
Anomaly detection and yield prediction across three public manufacturing datasets — a static snapshot (SECOM), in-process time series (PHM 2016 CMP), and a production routing graph (Bosch). Structure-driven method selection, leakage-safe temporal splits, and the diagnostics that overturned four apparent wins.
🏭 플라즈마 식각 공정 디지털 트윈 & 가상 계측 | PHM 2018 Ion Mill Etch | LightGBM RUL R²=1.0000 | XAI | Streamlit Dashboard
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